A novel framework for highly contagious diseases deaths prediction using machine learning techniques

被引:0
|
作者
Hasan S. [1 ]
Siddiqui T. [2 ]
Mustaqeem M. [2 ]
Khan N.A. [3 ]
机构
[1] A.K.T.U., I.T.M College, Aligarh
[2] Department of Computer Science, Aligarh Muslim University (AMU), Aligarh
[3] Faculty of Engineering and Technology, Arunachal University of Studies, Namsai
关键词
COVID-19—Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); IFR—infection fatality rate; SIR—susceptible-infectious removed;
D O I
10.1007/s41870-023-01567-2
中图分类号
学科分类号
摘要
The recent pandemic has shown us how a new pathogen can infect previously infected individuals again and the current data systems do not account for that in the SIR Model. During the pandemic, one of the more significant concerns in developing nations was the survival and livelihoods of the people below the poverty line. As these people lacked the necessary means to endure the long and hard-hitting impact of the pandemic on the economy, it led to an inability to follow the official guidelines due to the eminent need for survival. However, this also had another repercussion: the increase in the spread of the disease caused spikes in the number of cases over time. This has led us to believe that by using the percentage of a country's population living under the poverty line, we may be able to hypothetically calculate the number of deaths in a future pandemic under similar economic and social conditions. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023.
引用
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页码:2795 / 2802
页数:7
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